TEAM_TRINOVA

application/team trinova/.projectlinkstore

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+{"data":[{"hit":0,"alias":"app.c","type":"FILE","data":"C:/Users/INDARAM SRI CHARITHA/SimplicityStudio/v5_workspace/.browser/ml_voice_control_light/app.c"},{"hit":0,"alias":"main.c","type":"FILE","data":"C:/Users/INDARAM SRI CHARITHA/SimplicityStudio/v5_workspace/.browser/ml_voice_control_light/main.c"},{"hit":0,"alias":"readme.md","type":"FILE","data":"C:/Users/INDARAM SRI CHARITHA/SimplicityStudio/v5_workspace/.browser/ml_voice_control_light/readme.md"},{"hit":0,"alias":"Post Build Editor","type":"TOOL","data":"postbuildeditor"},{"hit":0,"alias":"Pin Tool","type":"TOOL","data":"pintool"},{"hit":0,"alias":"Memory Editor","type":"TOOL","data":"memoryeditor"},{"hit":0,"alias":"Software Components","type":"NAVIGATION","data":"softwarecomponents"},{"hit":0,"alias":"docs.silabs.com","type":"EXTERNAL_URL","data":"https://docs.silabs.com/"}]}

application/team trinova/app.c

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+/***************************************************************************//**
+ * @file
+ * @brief Top level application functions
+ *******************************************************************************
+ * # License
+ * <b>Copyright 2021 Silicon Laboratories Inc. www.silabs.com</b>
+ *******************************************************************************
+ *
+ * The licensor of this software is Silicon Laboratories Inc. Your use of this
+ * software is governed by the terms of Silicon Labs Master Software License
+ * Agreement (MSLA) available at
+ * www.silabs.com/about-us/legal/master-software-license-agreement. This
+ * software is distributed to you in Source Code format and is governed by the
+ * sections of the MSLA applicable to Source Code.
+ *
+ ******************************************************************************/
+#include "app.h"
+#include "voice_control_light.h"
+
+/***************************************************************************//**
+ * Initialize application.
+ ******************************************************************************/
+void app_init(void)
+{
+  voice_control_light_init();
+}

application/team trinova/app.h

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+/***************************************************************************//**
+ * @file app.h
+ * @brief Top level application functions
+ *******************************************************************************
+ * # License
+ * <b>Copyright 2021 Silicon Laboratories Inc. www.silabs.com</b>
+ *******************************************************************************
+ *
+ * The licensor of this software is Silicon Laboratories Inc. Your use of this
+ * software is governed by the terms of Silicon Labs Master Software License
+ * Agreement (MSLA) available at
+ * www.silabs.com/about-us/legal/master-software-license-agreement. This
+ * software is distributed to you in Source Code format and is governed by the
+ * sections of the MSLA applicable to Source Code.
+ *
+ ******************************************************************************/
+
+#ifndef APP_H
+#define APP_H
+
+/***************************************************************************//**
+ * Initialize application.
+ ******************************************************************************/
+void app_init(void);
+
+#endif  // APP_H

application/team trinova/main.c

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+/***************************************************************************//**
+ * @file main.c
+ * @brief main() function.
+ *******************************************************************************
+ * # License
+ * <b>Copyright 2025 Silicon Laboratories Inc. www.silabs.com</b>
+ *******************************************************************************
+ *
+ * SPDX-License-Identifier: Zlib
+ *
+ * The licensor of this software is Silicon Laboratories Inc.
+ *
+ * This software is provided 'as-is', without any express or implied
+ * warranty. In no event will the authors be held liable for any damages
+ * arising from the use of this software.
+ *
+ * Permission is granted to anyone to use this software for any purpose,
+ * including commercial applications, and to alter it and redistribute it
+ * freely, subject to the following restrictions:
+ *
+ * 1. The origin of this software must not be misrepresented; you must not
+ *    claim that you wrote the original software. If you use this software
+ *    in a product, an acknowledgment in the product documentation would be
+ *    appreciated but is not required.
+ * 2. Altered source versions must be plainly marked as such, and must not be
+ *    misrepresented as being the original software.
+ * 3. This notice may not be removed or altered from any source distribution.
+ *
+ ******************************************************************************/
+#include "sl_main_init.h"
+#include "sl_main_kernel.h"
+
+int main(void)
+{
+  // Initialize Silicon Labs device, system, service(s) and protocol stack(s).
+  sl_main_second_stage_init();
+
+  app_init();
+
+  while (sl_main_start_task_should_continue()) {
+    app_process_action();
+  }
+}

application/team trinova/ml_voice_control_light.pintool

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+<?xml version="1.0" encoding="ASCII"?>
+<device:XMLDevice xmi:version="2.0" xmlns:xmi="http://www.omg.org/XMI" xmlns:device="http://www.silabs.com/ss/hwconfig/document/device.ecore" name="pin_tool.EFR32MG26B510F3200IM68" partId="mcu.arm.efr32.mg26.efr32mg26b510f3200im68" contextId="com.silabs.sdk.stack.sisdk:2025.6.2._-662044072">
+  <mode name="DefaultMode">
+    <property object="DefaultMode" propertyId="mode.diagramLocation" value="100, 100"/>
+  </mode>
+  <modeTransition>
+    <property object="RESET &#x2192; DefaultMode" propertyId="modeTransition.source" value="RESET"/>
+    <property object="RESET &#x2192; DefaultMode" propertyId="modeTransition.target" value="DefaultMode"/>
+  </modeTransition>
+</device:XMLDevice>

application/team trinova/ml_voice_control_light.slcp

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+# Silicon Labs Project Configuration Tools: slcp, v0, Component selection file.
+project_name: ml_voice_control_light
+label: ml_voice_control_light
+description: |
+  This application uses TensorFlow Lite for Microcontrollers to detect the spoken words "on" and "off" from audio data recorded on the microphone in a Micrium OS kernel task. The detected keywords are used to control an LED on the board.
+category: AI/ML Application
+filter:
+- name: Capability
+  value: [Machine Learning]
+- name: Device Type
+  value: [SoC]
+- name: MCU
+  value: [32-bit MCU]
+- name: Project Difficulty
+  value: [Advanced]
+package: aiml
+quality: production
+readme:
+- {path: readme.md}
+- {path: readme.md}
+source:
+- {path: app.c}
+- {path: voice_control_light.cc}
+- {path: recognize_commands.cc}
+tag: ['hardware:device:flash:130', 'hardware:device:ram:128', 'hardware:component:microphone',
+  'hardware:component:led:1+']
+include:
+- path: .
+  file_list:
+  - {path: app.h}
+  - {path: voice_control_light.h}
+  - {path: recognize_commands.h}
+sdk: {id: simplicity_sdk, version: 2025.6.2}
+toolchain_settings:
+- {value: -Wno-unused-parameter, option: gcc_compiler_option}
+- {value: -Wno-missing-field-initializers, option: gcc_compiler_option}
+component:
+- {from: aiml, id: ml_audio_feature_generation}
+- {from: aiml, id: tensorflow_debug_log_iostream}
+- {from: aiml, id: tensorflow_lite_micro}
+- {from: aiml, id: tensorflow_lite_micro_accelerated_kernels}
+- {from: aiml, id: tensorflow_lite_micro_optimized_kernels}
+- {id: EFR32MG26B510F3200IM68}
+- {id: brd2608a}
+- {id: clock_manager}
+- {id: device_init}
+- {id: iostream_recommended_stream}
+- {id: iostream_retarget_stdio}
+- {id: memory_manager}
+- {id: micriumos_kernel}
+- {id: power_manager}
+- {id: printf}
+- instance: [led0]
+  id: simple_led
+- {id: sl_main}
+- {id: sleeptimer}
+- {id: status}
+define:
+- {name: DEBUG_EFM}
+- {name: TF_LITE_STATIC_MEMORY}
+config_file:
+- {path: config/recognize_commands_config.h}
+- {path: config/tflite/keyword_spotting_on_off_v2.tflite, directory: tflite}
+configuration:
+- {name: SL_BOARD_ENABLE_VCOM, value: '1'}
+- {name: SL_BOARD_ENABLE_SENSOR_MICROPHONE, value: '1'}
+- condition: [iostream_usart]
+  name: SL_IOSTREAM_USART_VCOM_CONVERT_BY_DEFAULT_LF_TO_CRLF
+  value: '1'
+- condition: [iostream_uart]
+  name: SL_IOSTREAM_UART_VCOM_CONVERT_BY_DEFAULT_LF_TO_CRLF
+  value: '1'
+- {name: SL_ML_AUDIO_FEATURE_GENERATION_AUDIO_BUFFER_SIZE, value: '4096'}
+- {name: SL_TFLITE_MICRO_ARENA_SIZE, value: '100000'}
+- {name: SL_HEAP_SIZE, value: '8192'}
+- condition: [tensorflow_lite_micro_accelerated_kernels]
+  name: SL_MVP_OPTIMIZE_SPEED
+  value: '1'
+ui_hints:
+  highlight:
+  - {path: readme.md, focus: true}
+sdk_extension:
+- {id: aiml, version: 2.1.2}
+

application/team trinova/ml_voice_control_light.slps

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+<?xml version="1.0" encoding="ASCII"?>
+<model:MDescriptors xmlns:model="http://www.silabs.com/ss/Studio.ecore">
+  <descriptors name="ml_voice_control_light">
+    <properties key="projectCommon.sdkId" value="com.silabs.sdk.stack.sisdk:2025.6.2._-662044072"/>
+    <properties key="universalConfig.relativeWorkspacePath" value="..\ml_voice_control_light.slcw"/>
+    <properties key="universalConfig.generationDirectory" value=""/>
+    <properties key="universalConfig.toolchainCompatibility" value="gcc"/>
+    <properties key="projectCommon.overwriteCopiedSources" value="false"/>
+    <properties key="projectCommon.boardIds" value="brd2608a:0.0.0.A02"/>
+    <properties key="projectCommon.kitId" value=""/>
+    <properties key="projectCommon.partId" value="mcu.arm.efr32.mg26.efr32mg26b510f3200im68"/>
+    <properties key="projectCommon.toolchainId" value="com.silabs.ss.tool.ide.arm.toolchain.gnu.cdt:12.2.1.20221205"/>
+    <properties key="universalConfig.projectTypeIds" value="com.silabs.ss.framework.ide.project.core.cdtMbsProjectType"/>
+    <properties key="projectCommon.importModeId" value="LINK_LIBRARIES"/>
+    <properties key="universalConfig.compSelProjInstanceId" value="1763969429120"/>
+  </descriptors>
+</model:MDescriptors>

application/team trinova/readme.md

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+# Voice Control Light
+This application uses TensorFlow Lite for Microcontrollers to detect the spoken
+words "on" and "off" from audio data recorded on the microphone. The detected
+keywords are used to control an LED on the board.
+
+Audio is sampled continuously from the microphone at a rate of 8kHz. The
+frequency components are then extracted by calculating the FFT on short segments
+of audio as they become available. The result is an array of filterbanks,
+representing the frequency components of the past second of audio. The processed
+audio data is passed into a neural network at an interval of 200 ms. If the
+model detects that either of the keywords "on" or "off" were spoken, LED0 will
+toggle accordingly and the keyword detection result is printed on VCOM.
+
+The application is based on TensorFlow's example application, **[micro speech](https://github.com/tensorflow/tensorflow/tree/v2.3.1/tensorflow/lite/micro/examples/micro_speech)**.
+
+## Model
+The application uses one of two different available models
+(```keyword_spotting_on_off.tflite``` or ```keyword_spotting_on_off_v2.tflite```)
+as the default model, depending on whether the application is generated for a
+development board featuring an MVP hardware accelerator or not. When an MVP
+hardware accelerator is featured on the board, inference will run at a faster
+speed such that a larger model can be chosen, yielding more accurate keyword
+detections.
+
+The neural network model has been trained to identify the two keywords "on" and
+"off" from preprocessed audio data. When neither words are recognized, the model
+will classify the input as either "unknown" or "background". The model takes an
+array of filterbanks as input and outputs a vector with each value corresponding
+to the probability that the input belongs to each of the
+categories.
+
+Details about the model architectures and scripts for generating the models can
+be found in the [Silicon Labs machine learning applications](https://github.com/SiliconLabs/machine_learning_applications/tree/main/) repository, under
+```application/voice/keyword_spotting/model```.

application/team trinova/recognize_commands.cc

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+/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
+
+   This file has been modified by Silicon Labs.
+   ==============================================================================*/
+
+#include "recognize_commands.h"
+
+#include <limits>
+
+// Labels used by the Voice Control tflite model
+// 0 - on
+// 1 - off
+// 2 - unknown
+// 3 - background
+const char* kCategoryLabels[kMaxCategoryCount] = {
+  "on",
+  "off",
+  "unknown",
+  "background",
+};
+
+RecognizeCommands::RecognizeCommands(tflite::ErrorReporter* error_reporter,
+                                     uint8_t detection_threshold,
+                                     int32_t suppression_ms)
+  : error_reporter_(error_reporter),
+  detection_threshold_(detection_threshold),
+  suppression_ms_(suppression_ms),
+  previous_results_(error_reporter)
+{
+  previous_top_label_index_ = 3; // "background"
+  previous_top_label_time_ = std::numeric_limits < int32_t > ::min();
+}
+
+TfLiteStatus RecognizeCommands::ProcessLatestResults(
+  const TfLiteTensor* latest_results, const int32_t current_time_ms,
+  uint8_t* found_command_index, uint8_t* score, bool* is_new_command)
+{
+
+uint8_t category_count = latest_results->dims->data[1];
+int8_t current_top_index = 0;
+int32_t current_top_score = 0;
+uint8_t converted_scores[kMaxCategoryCount];
+
+// Convert the model output to uint8
+if (latest_results->type == kTfLiteInt8) {
+    for(int i = 0; i < category_count; ++i) {
+      converted_scores[i] = (uint8_t)(latest_results->data.int8[i] + 128);
+    }
+  } else {
+      TF_LITE_REPORT_ERROR(error_reporter_, "Unsupported output tensor data type, must be int8 or float32");
+      return kTfLiteError;
+  }
+
+  for (int i = 0; i < category_count; i++) {
+    if (converted_scores[i] > current_top_score) {
+      current_top_score = converted_scores[i];
+      current_top_index = i;
+    }
+  }
+
+  // If we've recently had another label trigger, assume one that occurs too
+  // soon afterwards is a bad result.
+  int64_t time_since_last_top;
+  if ((previous_top_label_index_ == 3 || previous_top_label_index_ == 2)
+      || (previous_top_label_time_ == std::numeric_limits < int32_t > ::min())) {
+    time_since_last_top = std::numeric_limits < int32_t > ::max();
+    // Reset timer if detecting background / unknown
+  } else {
+    time_since_last_top = current_time_ms - previous_top_label_time_;
+  }
+
+  if ((current_top_score > detection_threshold_) && (time_since_last_top > suppression_ms_)) {
+    previous_top_label_index_ = current_top_index;
+    previous_top_label_time_ = current_time_ms;
+    *is_new_command = true;
+  } else {
+    *is_new_command = false;
+  }
+
+  *found_command_index = current_top_index;
+  *score = current_top_score;
+  return kTfLiteOk;
+}